1.101 – Le produit intérieur brut et ses composantes à prix courants (En milliards d’euros)

Données - INSEE

Auteur

François Geerolf

Info

  • Comptes de la Nation 2021. html

  • Comptes de la Nation 2020. html

  • Comptes de la Nation 2019. html

2020

Désordonné

Code 
t_1101 |>
  left_join(gdp, by = "date") |>
  filter(date == as.Date("2020-01-01")) |>
  select(-date) %>%
  mutate(`% du PIB` = (100*value/gdp) |> round(digits = 2) |> paste0(" %"),
         value = round(value) |> paste0(" Mds€")) |>
  select(-gdp) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

Ordre

Code 
t_1101 |>
  left_join(gdp, by = "date") |>
  filter(date == as.Date("2020-01-01")) |>
  select(-date) |>
  arrange(-value) %>%
  mutate(`% du PIB` = (100*value/gdp) |> round(digits = 2) |> paste0(" %"),
         value = round(value) |> paste0(" Mds€")) |>
  select(-gdp) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

2019

Désordonné

Code 
t_1101 |>
  left_join(gdp, by = "date") |>
  filter(date == as.Date("2019-01-01")) |>
  select(-date) %>%
  mutate(`% du PIB` = (100*value/gdp) |> round(digits = 2) |> paste0(" %"),
         value = round(value) |> paste0(" Mds€")) |>
  select(-gdp) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

Ordre

Code 
t_1101 |>
  left_join(gdp, by = "date") |>
  filter(date == as.Date("2019-01-01")) |>
  select(-date) |>
  arrange(-value) %>%
  mutate(`% du PIB` = (100*value/gdp) |> round(digits = 2) |> paste0(" %"),
         value = round(value) |> paste0(" Mds€")) |>
  select(-gdp) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F) else .}

Administration publique: Dépenses collective et individuelle

Code 
t_1101 |>
  filter(line %in% c(8, 10, 9)) |>
  left_join(gdp, by = "date") |>
  ggplot() + theme_minimal() + ylab("% du PIB") + xlab("") +
  geom_line(aes(x = date, y = value/gdp, color = Line, linetype = Line)) +
  theme(legend.title = element_blank(),
        legend.position = c(0.2, 0.85)) +
  scale_x_date(breaks = seq(1950, 2100, 5) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  scale_color_manual(values = viridis(4)[1:3]) +
  scale_y_log10(breaks = 0.01*seq(0, 100, 1),
                     labels = scales::percent_format(accuracy = 1))

GDP Components

Code 
t_1101 |>
  filter(line %in% c(8, 12, 9)) |>
  left_join(gdp, by = "date") |>
  ggplot() + theme_minimal() + ylab("% du PIB") + xlab("") +
  geom_line(aes(x = date, y = value/gdp, color = Line, linetype = Line)) +
  theme(legend.title = element_blank(),
        legend.position = c(0.7, 0.15)) +
  scale_x_date(breaks = seq(1950, 2100, 5) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  scale_color_manual(values = viridis(4)[1:3]) +
  scale_y_log10(breaks = 0.01*seq(0, 100, 1),
                     labels = scales::percent_format(accuracy = 1))

Investissement et taux de marge

Code 
t_1101 |>
  filter(line %in% c(12)) |>
  left_join(gdp, by = "date") |>
  mutate(value = value/gdp) |>
  select(Variable = Line, date, value) |>
  mutate(Variable = "Investissement (% du PIB)") |>
  bind_rows(t_txmargesnf_val |>
              filter(variable == "taux_marge") |>
              mutate(Variable = "Taux de marge") |>
              mutate(value = value/100)) |>
  ggplot() + theme_minimal() + ylab("") + xlab("") +
  geom_line(aes(x = date, y = value, color = Variable)) +
  theme(legend.title = element_blank(),
        legend.position = c(0.3, 0.9)) +
  scale_x_date(breaks = seq(1950, 2100, 5) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  scale_color_manual(values = viridis(3)[1:2]) +
  scale_y_continuous(breaks = 0.01*seq(0, 100, 1),
                     labels = scales::percent_format(accuracy = 1))